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        <h1>PySNN Documentation</h1>
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<h1 id="index">Index</h1>

<div class="genindex-jumpbox">
 <a href="#A"><strong>A</strong></a>
 | <a href="#B"><strong>B</strong></a>
 | <a href="#C"><strong>C</strong></a>
 | <a href="#D"><strong>D</strong></a>
 | <a href="#E"><strong>E</strong></a>
 | <a href="#F"><strong>F</strong></a>
 | <a href="#I"><strong>I</strong></a>
 | <a href="#L"><strong>L</strong></a>
 | <a href="#M"><strong>M</strong></a>
 | <a href="#N"><strong>N</strong></a>
 | <a href="#O"><strong>O</strong></a>
 | <a href="#P"><strong>P</strong></a>
 | <a href="#R"><strong>R</strong></a>
 | <a href="#S"><strong>S</strong></a>
 | <a href="#T"><strong>T</strong></a>
 | <a href="#U"><strong>U</strong></a>
 | <a href="#X"><strong>X</strong></a>
 
</div>
<h2 id="A">A</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="connection_reference.html#pysnn.connection.Conv2d.activation_potential">activation_potential() (pysnn.connection.Conv2d method)</a>

      <ul>
        <li><a href="connection_reference.html#pysnn.connection.Linear.activation_potential">(pysnn.connection.Linear method)</a>
</li>
      </ul></li>
      <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron">AdaptiveLIFNeuron (class in pysnn.neuron)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="connection_reference.html#pysnn.connection.AdaptiveMaxPool2d">AdaptiveMaxPool2d (class in pysnn.connection)</a>
</li>
      <li><a href="network_reference.html#pysnn.network.SNNNetwork.add_layer">add_layer() (pysnn.network.SNNNetwork method)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.AND">AND (class in pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="B">B</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseInput">BaseInput (class in pysnn.neuron)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron">BaseNeuron (class in pysnn.neuron)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.Boolean">Boolean (class in pysnn.datasets)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.BooleanNoise">BooleanNoise (class in pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="C">C</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="learning_reference.html#pysnn.learning.LearningRule.check_layers">check_layers() (pysnn.learning.LearningRule method)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.concat_trace">concat_trace() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection">Connection (class in pysnn.connection)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Conv2d">Conv2d (class in pysnn.connection)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="utils_reference.html#pysnn.utils.conv2d_output_shape">conv2d_output_shape() (in module pysnn.utils)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.convert_input">convert_input() (pysnn.neuron.BaseInput method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.convert_spikes">convert_spikes() (pysnn.connection.Connection method)</a>

      <ul>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.convert_spikes">(pysnn.neuron.BaseNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="D">D</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.DiscretizeFloat">DiscretizeFloat (class in pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="E">E</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="file_io_reference.html#pysnn.file_io.encode_1d_num_spikes">encode_1d_num_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.encode_1d_spikes">encode_1d_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.encode_2d_spikes">encode_2d_spikes() (in module pysnn.file_io)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="file_io_reference.html#pysnn.file_io.encode_3d_spikes">encode_3d_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.Events">Events (class in pysnn.file_io)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.exponential_thresh_update">exponential_thresh_update() (in module pysnn.functional)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.exponential_trace_update">exponential_trace_update() (in module pysnn.functional)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="F">F</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="functional_reference.html#pysnn.functional.fede_voltage_update">fede_voltage_update() (in module pysnn.functional)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.FedeNeuron">FedeNeuron (class in pysnn.neuron)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.FedeSTDP">FedeSTDP (class in pysnn.learning)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.fold">fold() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.AdaptiveMaxPool2d.forward">forward() (pysnn.connection.AdaptiveMaxPool2d method)</a>

      <ul>
        <li><a href="connection_reference.html#pysnn.connection.Conv2d.forward">(pysnn.connection.Conv2d method)</a>
</li>
        <li><a href="connection_reference.html#pysnn.connection.Linear.forward">(pysnn.connection.Linear method)</a>
</li>
        <li><a href="connection_reference.html#pysnn.connection.MaxPool2d.forward">(pysnn.connection.MaxPool2d method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron.forward">(pysnn.neuron.AdaptiveLIFNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.forward">(pysnn.neuron.BaseInput method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.forward">(pysnn.neuron.BaseNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.FedeNeuron.forward">(pysnn.neuron.FedeNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.IFNeuron.forward">(pysnn.neuron.IFNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.Input.forward">(pysnn.neuron.Input method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.LIFNeuron.forward">(pysnn.neuron.LIFNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="I">I</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="functional_reference.html#pysnn.functional.if_voltage_update">if_voltage_update() (in module pysnn.functional)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.IFNeuron">IFNeuron (class in pysnn.neuron)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.init_connection">init_connection() (pysnn.connection.Connection method)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.init_neuron">init_neuron() (pysnn.neuron.BaseInput method)</a>

      <ul>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.init_neuron">(pysnn.neuron.BaseNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.Input">Input (class in pysnn.neuron)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.Intensity">Intensity (class in pysnn.datasets)</a>
</li>
      <li><a href="utils_reference.html#pysnn.utils.interspike_time">interspike_time() (in module pysnn.utils)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="L">L</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="network_reference.html#pysnn.network.SNNNetwork.layer_state_dict">layer_state_dict() (pysnn.network.SNNNetwork method)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.LearningRule">LearningRule (class in pysnn.learning)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.lif_exponential_voltage_update">lif_exponential_voltage_update() (in module pysnn.functional)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.lif_linear_voltage_update">lif_linear_voltage_update() (in module pysnn.functional)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.LIFNeuron">LIFNeuron (class in pysnn.neuron)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Linear">Linear (class in pysnn.connection)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.linear_thresh_update">linear_thresh_update() (in module pysnn.functional)</a>
</li>
      <li><a href="functional_reference.html#pysnn.functional.linear_trace_update">linear_trace_update() (in module pysnn.functional)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="M">M</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="connection_reference.html#pysnn.connection.MaxPool2d">MaxPool2d (class in pysnn.connection)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="learning_reference.html#pysnn.learning.MSTDPET">MSTDPET (class in pysnn.learning)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="N">N</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.ncaltech_train_test">ncaltech_train_test() (in module pysnn.datasets)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.ncars_train_test">ncars_train_test() (in module pysnn.datasets)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.NeuromorphicDataset">NeuromorphicDataset (class in pysnn.datasets)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.nmnist_train_test">nmnist_train_test() (in module pysnn.datasets)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.no_grad">no_grad() (pysnn.connection.Connection method)</a>

      <ul>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.no_grad">(pysnn.neuron.BaseInput method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.no_grad">(pysnn.neuron.BaseNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="O">O</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.OR">OR (class in pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="P">P</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="encoding_reference.html#pysnn.encoding.poisson_encoding">poisson_encoding() (in module pysnn.encoding)</a>
</li>
      <li><a href="encoding_reference.html#pysnn.encoding.PoissonEncoder">PoissonEncoder (class in pysnn.encoding)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.LearningRule.pre_mult_post">pre_mult_post() (pysnn.learning.LearningRule method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.propagate_spike">propagate_spike() (pysnn.connection.Connection method)</a>
</li>
      <li><a href="connection_reference.html#module-pysnn.connection">pysnn.connection (module)</a>
</li>
      <li><a href="datasets_reference.html#module-pysnn.datasets">pysnn.datasets (module)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="encoding_reference.html#module-pysnn.encoding">pysnn.encoding (module)</a>
</li>
      <li><a href="file_io_reference.html#module-pysnn.file_io">pysnn.file_io (module)</a>
</li>
      <li><a href="functional_reference.html#module-pysnn.functional">pysnn.functional (module)</a>
</li>
      <li><a href="learning_reference.html#module-pysnn.learning">pysnn.learning (module)</a>
</li>
      <li><a href="network_reference.html#module-pysnn.network">pysnn.network (module)</a>
</li>
      <li><a href="neuron_reference.html#module-pysnn.neuron">pysnn.neuron (module)</a>
</li>
      <li><a href="utils_reference.html#module-pysnn.utils">pysnn.utils (module)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="R">R</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="file_io_reference.html#pysnn.file_io.read_1d_num_spikes">read_1d_num_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.read_1d_spikes">read_1d_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.read_2d_spikes">read_2d_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.read_3d_spikes">read_3d_spikes() (in module pysnn.file_io)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.LearningRule.reduce_connections">reduce_connections() (pysnn.learning.LearningRule method)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.refrac">refrac() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.reset_state">reset_state() (pysnn.connection.Connection method)</a>

      <ul>
        <li><a href="learning_reference.html#pysnn.learning.LearningRule.reset_state">(pysnn.learning.LearningRule method)</a>
</li>
        <li><a href="learning_reference.html#pysnn.learning.MSTDPET.reset_state">(pysnn.learning.MSTDPET method)</a>
</li>
        <li><a href="network_reference.html#pysnn.network.SNNNetwork.reset_state">(pysnn.network.SNNNetwork method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron.reset_state">(pysnn.neuron.AdaptiveLIFNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.reset_state">(pysnn.neuron.BaseInput method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.reset_state">(pysnn.neuron.BaseNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.reset_thresh">reset_thresh() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="connection_reference.html#pysnn.connection.Connection.reset_weights">reset_weights() (pysnn.connection.Connection method)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="S">S</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="file_io_reference.html#pysnn.file_io.show_td">show_td() (in module pysnn.file_io)</a>
</li>
      <li><a href="network_reference.html#pysnn.network.SNNNetwork">SNNNetwork (class in pysnn.network)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.spike_array_to_events">spike_array_to_events() (in module pysnn.file_io)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.spiking">spiking() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.FedeSTDP.step">step() (pysnn.learning.FedeSTDP method)</a>

      <ul>
        <li><a href="learning_reference.html#pysnn.learning.LearningRule.step">(pysnn.learning.LearningRule method)</a>
</li>
        <li><a href="learning_reference.html#pysnn.learning.MSTDPET.step">(pysnn.learning.MSTDPET method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="T">T</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="utils_reference.html#pysnn.utils.tensor_clamp">tensor_clamp() (in module pysnn.utils)</a>
</li>
      <li><a href="file_io_reference.html#pysnn.file_io.Events.to_spike_array">to_spike_array() (pysnn.file_io.Events method)</a>
</li>
  </ul></td>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="file_io_reference.html#pysnn.file_io.Events.to_spike_tensor">to_spike_tensor() (pysnn.file_io.Events method)</a>
</li>
      <li><a href="datasets_reference.html#pysnn.datasets.train_test">train_test() (in module pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>

<h2 id="U">U</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.unfold">unfold() (pysnn.neuron.BaseNeuron method)</a>
</li>
      <li><a href="learning_reference.html#pysnn.learning.LearningRule.update_state">update_state() (pysnn.learning.LearningRule method)</a>

      <ul>
        <li><a href="learning_reference.html#pysnn.learning.MSTDPET.update_state">(pysnn.learning.MSTDPET method)</a>
</li>
      </ul></li>
      <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron.update_thresh">update_thresh() (pysnn.neuron.AdaptiveLIFNeuron method)</a>
</li>
      <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron.update_trace">update_trace() (pysnn.neuron.AdaptiveLIFNeuron method)</a>

      <ul>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseInput.update_trace">(pysnn.neuron.BaseInput method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.update_trace">(pysnn.neuron.BaseNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.FedeNeuron.update_trace">(pysnn.neuron.FedeNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.IFNeuron.update_trace">(pysnn.neuron.IFNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.Input.update_trace">(pysnn.neuron.Input method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.LIFNeuron.update_trace">(pysnn.neuron.LIFNeuron method)</a>
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  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="neuron_reference.html#pysnn.neuron.AdaptiveLIFNeuron.update_voltage">update_voltage() (pysnn.neuron.AdaptiveLIFNeuron method)</a>

      <ul>
        <li><a href="neuron_reference.html#pysnn.neuron.BaseNeuron.update_voltage">(pysnn.neuron.BaseNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.FedeNeuron.update_voltage">(pysnn.neuron.FedeNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.IFNeuron.update_voltage">(pysnn.neuron.IFNeuron method)</a>
</li>
        <li><a href="neuron_reference.html#pysnn.neuron.LIFNeuron.update_voltage">(pysnn.neuron.LIFNeuron method)</a>
</li>
      </ul></li>
  </ul></td>
</tr></table>

<h2 id="X">X</h2>
<table style="width: 100%" class="indextable genindextable"><tr>
  <td style="width: 33%; vertical-align: top;"><ul>
      <li><a href="datasets_reference.html#pysnn.datasets.XOR">XOR (class in pysnn.datasets)</a>
</li>
  </ul></td>
</tr></table>



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